Level-Set-Based Topology Optimization Using Remeshing Techniques for Magnetic Actuator Design

Seungmin Jeong,Sunghoon Lim,Seungjae Min IEEE 2016 IEEE transactions on magnetics Vol.52 No.3

<P>This paper proposes a new level-set-based topology optimization method for magnetic actuator design using remeshing techniques that can generate meshes on the exact structural boundaries to improve the accuracy of finite-element analysis. Two remeshing techniques, such as the modified adaptive mesh method and the extended finite-element method (XFEM), are introduced for the optimization process. To control the computational time with meshing that is economical and analysis that is accurate, a new resolution parameter that can manage the level of mesh density around the level-set boundaries is employed in the modified adaptive mesh method. In the XFEM, the enrichment term in the element shape function is employed to track the exact outer boundary of the actuator. The optimization problem is formulated to maximize the magnetic force between the core and an armature under the volume constraint of the ferromagnetic material. To verify the effectiveness of the proposed method, it is applied to an electromagnetic problem for an optimal C-core actuator design that is very sensitive to structural boundaries.</P>

Development of a Hybrid Deep-Learning Model for the Human Activity Recognition based on the Wristband Accelerometer Signals

( Seungmin Jeong ),( Dongik Oh ) 한국인터넷정보학회 2021 인터넷정보학회논문지 Vol.22 No.3

This study aims to develop a human activity recognition (HAR) system as a Deep-Learning (DL) classification model, distinguishing various human activities. We solely rely on the signals from a wristband accelerometer worn by a person for the user's convenience. 3-axis sequential acceleration signal data are gathered within a predefined time-window-slice, and they are used as input to the classification system. We are particularly interested in developing a Deep-Learning model that can outperform conventional machine learning classification performance. A total of 13 activities based on the laboratory experiments' data are used for the initial performance comparison. We have improved classification performance using the Convolutional Neural Network (CNN) combined with an auto-encoder feature reduction and parameter tuning. With various publically available HAR datasets, we could also achieve significant improvement in HAR classification. Our CNN model is also compared against Recurrent-Neural-Network(RNN) with Long Short-Term Memory(LSTM) to demonstrate its superiority. Noticeably, our model could distinguish both general activities and near-identical activities such as sitting down on the chair and floor, with almost perfect classification accuracy.

Correlations between regional characteristics of counties and the ratio of intracounty to extracounty sources of COVID-19 in Gangwon Province, Republic of Korea

Seungmin Jeong,Chaeyun Lim,Sunhak Bae,Youngju Nam,Eunmi Kim,Myeonggi Kim,Saerom Kim,Yeojin Kim 질병관리본부 2023 Osong Public Health and Research Persptectives Vol.14 No.3

Objectives: This study aimed to examine the correlations between the regional characteristics of counties in Gangwon Province, Republic of Korea and the ratio of intracounty to extracounty sources of coronavirus disease 2019 (COVID-19) infection.Methods: The region of the infectious contact was analysed for each COVID-19 case reported in Gangwon Province between February 22, 2020 and February 7, 2022. The population, population density, area, the proportion of urban residents, the proportion of older adults (>65 years), financial independence, and the number of adjacent counties were assessed for each of the 18 counties in Gangwon Province. Correlation coefficients between regional characteristics and the ratio of intracounty to extracounty infections were calculated.Results: In total, 19,645 cases were included in this study. The population, population density, proportion of older adults, and proportion of urban residents were significantly correlated with the ratio of intracounty to extracounty infections. A stratified analysis with an age cut-point of 65 years showed that the proportion of older adults had a significant negative correlation with the ratio of intracounty to extracounty infections. In other words, the proportions of extracounty infections were higher in countries with higher proportions of older adults.Conclusion: Regions with ageing populations should carefully observe trends in infectious disease outbreaks in other regions to prevent possible transmission.

Concordance in the Health Behaviors of Couples by Age: A Cross-sectional Study

Jeong, Seungmin,Cho, Sung-il The Korean Society for Preventive Medicine 2018 Journal of Preventive Medicine and Public Health Vol.51 No.1

Objectives: To investigate concordance in the health behaviors of women and their partners according to age and to investigate whether there was a stronger correlation between the health behaviors of housewives and those of their partners than between the health behaviors of non-housewives and those of their partners. Methods: We used data obtained from women participants in the 2015 Korea Community Health Survey who were living with their partners. The outcome variables were 4 health behaviors: smoking, drinking, eating salty food, and physical activity. The main independent variables were the partners' corresponding health behaviors. We categorized age into 4 groups (19-29, 30-49, 50-64, and ${\geq}65\;years$) and utilized multivariate logistic regression analysis, stratifying by age group. Another logistic regression analysis was stratified by whether the participant identified as a housewife. Results: Data from 64 971 women older than 18 years of age were analyzed. Of the 4 health behaviors, the risk of smoking (adjusted odds ratio [aOR], 4.65; 95% confidence interval [CI], 3.93 to 5.49) was highest when the participant's partner was also a smoker. Similar results were found for an inactive lifestyle (aOR, 2.56; 95% CI, 2.45 to 2.66), eating salty food (aOR, 2.48; 95% CI, 2.36 to 2.62); and excessive drinking (aOR, 1.89; 95% CI, 1.80 to 1.98). In comparison to non-housewives, housewives had higher odds of eating salty food. Conclusions: The health behaviors of women were positively correlated with those of their partners. The magnitude of the concordance differed by age group.

배터리 수명을 고려한 OLEV 시스템 디자인

Seungmin Jeong(정승민),Young Jae Jang(장영재) 대한산업공학회 2014 대한산업공학회 추계학술대회논문집 Vol.2014 No.11

Effects of living alone versus with others and of housemate type on smoking, drinking, dietary habits, and physical activity among elderly people

Seungmin Jeong,Sung il Cho 한국역학회 2017 Epidemiology and Health Vol.39 No.-

OBJECTIVES: This study examined differences in health behaviors between elderly people living alone and with others; it also investigated whether the effect of living with others differs according to housemate type, namely a spouse and/or younger generations. METHODS: Gender-stratified data from the 2013 Korea Community Health Survey for individuals aged 60 to 74 living in Seoul were analyzed. Logistic regression modeling was conducted to obtain odds ratios (ORs) and 95% confidence intervals (CIs) of the outcome variables (smoking, drinking, eating salty foods, inactive lifestyle) for the variables of interest (living alone/with others, housemate type). Models were adjusted for confounding variables including history of medical conditions, employment type, and adjusted household income. RESULTS: Analysis involved 1,814 men and 2,199 women. Risk of smoking was 1.80 times (95% CI, 1.21 to 2.67) higher for men living alone than living with others. Risk of eating salty foods was 0.78 times lower (95% CI, 0.62 to 0.98) for men living with a spouse than a spouse and younger generations. Risk of inactive lifestyle was 1.47 times higher (95% CI, 1.13 to 1.92) for women living alone. Risk of smoking was higher for women living alone (OR, 1.41; 95% CI, 1.03 to 1.92) or with younger generations (OR, 9.12; 95% CI, 2.04 to 40.80) than with a spouse and younger generations. CONCLUSIONS: Living alone was associated with smoking in men and physical activity in women; housemate type was associated with dietary habits in men and smoking in women. These gender-specific findings can help identify groups of individuals vulnerable to risky health behaviors and to develop policies.

Charging Automation for Electric Vehicles: Is a Smaller Battery Good for the Wireless Charging Electric Vehicles?

Jeong, Seungmin,Jang, Young Jae,Kum, Dongsuk,Lee, Min Seok IEEE 2019 IEEE transactions on automation science and engine Vol.16 No.1

<P>Dynamic wireless charging (DWC) is an emerging technology that enables the batteries of electric vehicles (EVs) to charge automatically while the vehicles are in motion. The DWC-EV system addresses the challenges inherent in battery technology, such as the short driving range, long recharging time, and high price. Compared with conventional plug-in EVs, the DWC-EV can charge a battery more frequently because it can be done while the EV is in motion from the charging infrastructure installed on the road. In this paper, we analyze how this frequent-charging characteristic of DWC-EV can affect the battery lifetime in the DWC-EV. We first introduce a mathematical model to evaluate the economic cost of the DWC-EV for a given battery size. A battery degradation model is incorporated to account for the quantitative relationship between the installation of the charging infrastructure and battery life extension. We then use the model to analyze how the economic cost varies with the size of the battery. Our preliminary findings provide insight into the relationship between DWC from the charging infrastructure and the battery’s lifetime. <I>Note to Practitioners</I>—There is a tradeoff between power track allocation and battery size in DWC buses. It has been known that DWC buses need not equip a large battery because the battery can be charged frequently from the power track along the route. Also, it has been agreed that frequent shallow charging with DWC can improve the battery’s lifetime compared to infrequent deep charging. We verify these common beliefs and agreement with a mathematical approach with a widely used battery lifetime estimation model. Our quantitative model indicates that the DWC can positively improve battery lifetime, but this positive effect is always true only when the battery is large enough, even if the battery is charged frequently with DWC. The presented optimization model suggests that the lifelong economic benefit of DWC-based bus transit can be realized with optimal allocation of the power track with a sufficiently large battery.</P>

웨어러블 기기를 위한 광혈류 데이터 기반 혈압 측정 하이브리드 딥러닝 시스템의 구축

정승민(Seungmin Jeong),김영(Young Kim),조은혜(Eun Hye Jo),민세동(Se Dong Min) 대한전기학회 2021 전기학회논문지 Vol.70 No.8

In this work, we developed a PPG-based blood pressure estimation hybrid deep learning model built into wearable devices and used by hypertension patients to monitor blood pressure in real-time in their daily lives. The model is a deep-learning model that combines data preprocessing, Autoencoder deep learning model for feature extraction, and RAN regression model developed by this research team. We conducted experiments to compare the blood pressure prediction performance of the proposed model with other deep learning models and find out how the objective blood pressure prediction performance is. We conducted experiments on an open dataset with the vital signs of 32 subjects. After models trained on 24 subjects’ data and are tested on eight other people’s data, we could see that using deep-learning regression models combined with an Autoencoder (hybrid deep-learning) performs better than using a deep learning model alone, and RAN accurately predicts blood pressure than the comparable deep-learning models. The study found that the average error for actual and predicted blood pressure in the proposed hybrid deep-learning models was 4.67 mmHg, and the standard deviation of error was 6.37 mmHg. It satisfies the accuracy criteria presented by the Korean National Institute of Food and Drug Safety Evaluation.

방향을 가진 물체 인식 알고리즘과 조립 전략을 활용한 단일 하네스 케이블 조립 공정

이승민(Seungmin Lee),정앤드류(Andrew Jeong),정석환(Seokhwan Jeong) 국방로봇학회 2023 국방로봇학회 논문집 Vol.2 No.2

복합재 압력용기의 성능지수 최대화를 위한 적층 설계변수 연구

정승민(Seungmin Jeong),황태경(Taekyung Hwang) 한국추진공학회 2017 한국추진공학회 학술대회논문집 Vol.2017 No.5

본 연구에서는 복합재 압력용기의 성능지수를 최대화하기 위한 적층 설계변수의 영향도 평가 및 최적설계를 수행하였다. 복합재 압력용기의 성능지수에는 용기의 내부체적을 포함한 내압성능 및 경량화 개념이 함축되어 있다. 따라서 성능지수를 최대화하기 위하여 압력용기의 내부체적이 고정되어 있다는 가정 하에 헬리컬 및 후프 층의 두께와 후프 층의 길이, 총 세 가지 변수를 고려하였다. 선정된 변수들의 최적화를 위하여 대체모델의 구축에 필요한 반응표면법이 도입되었고, 변수의 영향도를 평가하기 위한 분산분석이 수행되었다. 최적설계 문제는 내압성능 제약조건 하에 성능지수를 최대화하는 문제로 정식화하였다. 도출된 최적화 모델에 대한 추가적인 수치해석을 통해 본 연구의 효용성을 입증하였다. In this paper the laminate design parameters are researched to maximize the performance index of a composite pressure vessel. The pressure-resistant performance and the light-weight concept with contained internal space are implied in the performance index. To maximize the performance index, the three design variables that the thickness of each of helical and hoop layers and the length of hoop layer are considered under the assumption of fixed internal space. To optimize the variables, the response surface method is introduced for construction of the surrogate model and the ANOVA(analysis of variance) is performed to evaluate the effects of the variables. The optimization problem is formulated to maximize performance index under the burst pressure constraint. To verify the effectiveness of the research, numerical analyses are performed for the optimum model.